An Acceptable Trade-off between New Call Blocking and Handoff Call Dropping Probabilities in Multimedia Cellular Networks
Why this work is in the frame
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Bibliographic record
Abstract
Providing multimedia services with quality of service (QoS) guarantees in next generation wireless cellular networks poses great challenges due to the scarce radio bandwidth. Therefore, effective management of the limited radio resources is important to enhance the network performance. In this paper, we propose a dynamic bandwidth adaptation framework to provide an acceptable trade-off between new call blocking and handoff call dropping probabilities in cellular-based multimedia wireless networks. The proposed framework is designed to take advantage of the adaptive bandwidth allocation (ABA) algorithm with new calls in order to enhance the system utilization and blocking probability of new calls. The performance of our framework is compared to a framework previously proposed in N. Nasser, (2005). Simulation results show that our QoS adaptive multimedia service framework outperforms the previous framework in terms of new call blocking probability, handoff call dropping probability, and bandwidth utilization
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it